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Index Funds
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Categories, Factors, and Filters at a Glance
| Categories | Selections |
| Product Type | Funds and ETFs |
| Asset Type | Stock |
| Track Record | 3 Years |
| Domestic Equity | Small Cap, Blend |
| Criteria | K4 Factor | Importance |
| Major Drag on Net Return | Expense Ratio | High |
| Return | 3-Year Return +/- Category Index | Highest |
| Index Relative Risk | 3-Year Beta (Category Index) | Lowest |
| Downside Protection | 5-Year Down Market Ratio | Medium |
| Filter | Limits |
| Index or Active | Index |
| 3-Year R-Squared (Category Index) | ≥ 95 |
| 3-Year Relative Standard Deviation | ≤ 108 |
| Best Fit Index | Russell 2000 |
| Distinct Portfolio | Yes |
You’d think finding an index fund would be simple: It’s supposed to look and act like the index. You don’t care about high alphas or wild standard deviations. You’re not worried that the fund’s too concentrated or even if the manager has a long tenure. All index funds are essentially the same except for a few subtle differences, and that’s what you need to capture in your scenario.
Although you could create one giant scenario with all index funds and then use filters to get a specific category, you’ll get a more meaningful comparison if you limit your evaluation to a more specific category. As is always the case with K4 Fund Selection, once you’ve created your scenario, you can easily copy it over to other categories.
You can include both funds and ETFs in the scenario. Often you want to consider them separately because the ETFs won’t fare too well versus actively managed funds and their relatively low costs can skew the range of the expense ratios. But here you only want to consider index funds and low expenses are a definite plus.
Instead of using 5- or 10-year statistics, it’s better to stick with 3-year values given that many index funds don’t have exceptionally long track records. As opposed to an actively managed fund evaluation, it won’t make as much difference here because index funds tend to closely track their benchmarks in all market conditions.
Step By Step Guide
- Begin by selecting “Create New Scenario” and give it the name “Small Cap Blend Index Funds.”
- On the next screen, choose “Funds and ETFs” for the Product Type and “Stock” for the Asset Type. Change Track Record to “3 Years” to limit the analysis to funds with a minimum of three years’ history. Click on “Update Classes.”
- On the next screen, select “Small Cap” and “Blend” in the Domestic Equity section. Click on the “Update Selections” button at the bottom of the page and when it updates, click on the “Save Selections” button at the bottom of the page.
- Click “Continue” on the next two screens to bring you to the attribute selection page.
- Select the following K4 factors to reflect the associated investment criteria:
| Criteria | K4 Factor | Importance |
| Major Drag on Net Return | Expense Ratio | High |
| Return | 3-Year Return +/- Category Index | Highest |
| Index Relative Risk | 3-Year Beta (Category Index) | Lowest |
| Downside Protection | 5-Year Down Market Ratio | Medium |
- Click “Continue” and on the next page and select a method to weight the five factors. (Unless you already have some definite percentages in mind, the first option, “Complete the Preference Questionnaire,” is probably the best choice.) Provide the necessary responses for the selected method.
- On the Results page, click on “Add” to the right of Filter Status. Hold down the control key and select the following five filter items from the first column of the table below, then click on “Add Filter.”
| Filter | Limits |
| Index or Active | Index |
| 3-Year R-Squared (Category Index) | ≥ 95 |
| 3-Year Relative Standard Deviation | ≤ 108 |
| Best Fit Index | Russell 2000 |
| Distinct Portfolio | Yes |
- Enter the corresponding limit from the second column of the above table for each filter in the first column. Click on “Apply Filters” at the bottom of the page. This will take you back to your filtered results.
It might seem odd that Return +/- Category Index is the most heavily weighted factor. In the world of index funds, a few basis points can be a big differentiator. While most stay close to their benchmarks, minor differences between NAV and ask prices or an index fund’s asset-lending policies can add a few basis points here and there. Expense Ratio is important for the same reason. Any reduction there will have a noticeable impact on net return. It’s important that the fund’s beta be close to that of the index because you want the risk as well as the return to closely track the benchmark. The Down Market Ratio is included as a gauge of the fund’s ability to stick near the index when times are tough. Failure to do so can quickly leave the fund well below the index, a gap that will be difficult if not impossible to close.
Until the index filter is applied, the scenario covers all funds in the category. The Best Fit Index filter eliminates any funds with a best fit other than the Category Index. In putting this model together, we found several funds (particularly in the mid cap categories) where this occurred. You might be willing to accept an actively managed fund with a best fit outside the category, but that makes no sense if you are seeking an index fund to represent the category. The R-Squared filter also requires a high correlation with the index while the Relative Standard Deviation filter eliminates funds that are substantially riskier than the index.
For Other Categories
To use this same scenario for other categories (e.g. Large Cap Value):
- Click on “Back to Scenario Management” just below “Category Selection” the top left of the page.
- Locate the scenario you just created in the current folder and click “Copy.” On the next page, rename the scenario “Large Cap Value” and click continue. This will take you back to the original folder in Scenario Management.
- Locate the scenario you just renamed and click on “Edit.” Click “Continue” on the next page to return to the Category Selection page.
- Change the “Capitalization” from “Small Cap” to “Large Cap” and change “Blend” to “Value.” Click “Update Selections” at the bottom of the page and once it refreshes, click “Save Selections.”
- If you are reusing the same model, there is no need to go through the Preference tab. Instead proceed directly to the Results page where you can change the Best Fit Index filter from Russell 2000 to Russell l000 Value.
- Steps 1-5 can be repeated to create new scenarios for other categories by changing the capitalization and/or style in the Category Selection tab and the Best Fit filter on the Results tab.
Once you’ve established all your scenarios, you can then use them to monitor the funds. When it’s time to review them, simply copy and rename each scenario with the current date. When you open the new copy, you can proceed directly to the results page and view the updated data. The update is automatic and you don’t even need to answer the questions on the Category or Preference tabs. You can now compare the current results to those in the original scenario. This is also a simple means of creating an ongoing history of your analyses to track the funds over time.
Product Highlight - K4 Fund Selection
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Scoring Beats Screening for Mutual Fund Evaluation and Monitoring
For many investment professionals, mutual fund analysis, monitoring, and selection are an integral part of the services they provide. Like all investment decisions, this requires them to consider a number of different and often conflicting attributes. Long-term performance needs to be considered along with expense ratio and risk. Accurately measuring their relative importance and resolving the conflicts between them is a complex and difficult task. In addition, many are measured in different units making aggregation of the results impossible without a sophisticated scoring system. All of this can really only be accomplished with a clearly defined process that is quick, efficient, and objective. That is why these investment professionals need K4 Fund Selection.
K4 Fund Selection is an internet-based tool used to rank, evaluate and monitor mutual funds and ETFs. Unlike the pass/fail search and single point analysis methodologies used in other tools, K4 Fund Selection doesn’t simply eliminate funds based on equally-weighted stand-alone screens. Instead, it gives the user the ability to rigorously, objectively and easily create weighted factor models that score, rank and monitor funds on a number of attributes simultaneously. K4 Fund Selection yields a ranked list of all funds based on all their attributes and the importance the user places on each.
This ranking process not only resolves the major problems of pass/fail hurdles, but also eliminates the need to sort on individual attributes. With K4 Fund Selection’s comprehensive reporting and exporting capabilities, the user can quickly access a wealth of data for documentation, client presentations, and further analysis. When it’s time to re-evaluate or monitor funds, the entire process can be repeated with just a few clicks of the mouse, saving valuable time -- something most investment professionals can really use.
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